Lifeboat Foundation

OpenAI becomes the first firm to receive Nvidia’s cutting-edge AI DGX H200 GPU, fostering GPT-5’s advancement toward AGI.

The iconic Transformers villain comes to life in a self-converting robot that turns into a tank. It’s a killer toy.

This unveil marks a significant step towards the production of its new ultra-advanced 1.6-nanometer (nm) chips by 2026.

With its focus on nanosheet transistors and innovative backside power delivery, A16 paves the way for the production of 1.6nm chips by 2026.

Not many devices in the datacenter have been etched with the Intel 4 process, which is the chip maker’s spin on 7 nanometer extreme ultraviolet immersion lithography. But Intel’s Loihi 2 neuromorphic processor is one of them, and Sandia National Laboratories is firing up a supercomputer with 1,152 of them interlinked to create what Intel is calling the largest neuromorphic system every assembled.

With Nvidia’s top-end “Blackwell” GPU accelerators now pushing up to 1,200 watts in their peak configurations, and require liquid cooling, and other accelerators no doubt following as their sockets get inevitably bigger as Moore’s Law scaling for chip making slows, this is a good time to take a step back and see what can be done with a reasonably scaled neuromorphic system, which not only has circuits which act more like real neurons used in real brains and also burn orders of magnitude less power than the XPUs commonly used in the datacenter for all kinds of compute.

Google might have invented the transformer models that led to the glut of generative AI we see today, but it wasn’t the first to cash in. The search giant threw its AI work into overdrive in the wake of ChatGPT’s appearance in Microsoft products, adding the Gemini AI to every product it can. A new report claims Gemini is about to come to the Google app on Android, and this may signal the beginning of the end for Assistant.

Gemini is the current brand for all of Google’s commercial AI models—whether it sticks to that is hard to say, but the Bard branding is in the rearview mirror. Gemini has been available on the web, and Google released a mobile app earlier this year. Installing that app on Android prompts you to replace Assistant despite Gemini’s comparative lack of features. Google is just that committed to getting everyone using its AI. Even if you don’t install that app, Google aims to get Gemini in front of your eyes by cramming it into the Google app.

While there’s no official announcement yet, a video of the latest app update is already circulating (see below). The new version has a toggle at the top to switch between search and Gemini. If you’ve seen the iOS Google app recently, it’s essentially the same. There is another wrinkle for Android users, though. That toggle will also switch your phone to use Assistant everywhere, reports 9to5Google. The Google app will now encourage people to switch from Assistant to Gemini, and unlike the new Gemini app, it’s already installed on virtually every Android phone.

Elon Musk just dropped hints about Tesla’s robotaxi and humanoid robot efforts. If all goes well, both could change your workplace, and how you commute to it.

Apple today released several open source large language models (LLMs) that are designed to run on-device rather than through cloud servers. Called OpenELM (Open-source Efficient Language Models), the LLMs are available on the Hugging Face Hub, a community for sharing AI code.

As outlined in a white paper [PDF], there are eight total OpenELM models, four of which were pre-trained using the CoreNet library, and four instruction tuned models. Apple uses a layer-wise scaling strategy that is aimed at improving accuracy and efficiency.

Adobe researchers have developed a new generative AI model called VideoGigaGAN that can upscale blurry videos at up to eight times their original resolution. Introduced in a paper published on April 18th, Adobe claims VideoGigaGAN is superior to other Video Super Resolution (VSR) methods as it can provide more fine-grained details without introducing any “AI weirdness” to the footage.

In a nutshell, Generative Adversarial Networks (GANs) are effective for upscaling still images to a higher resolution, but struggle to do the same for video without introducing flickering and other unwanted artifacts. Other upscaling methods can avoid this, but the results aren’t as sharp or detailed. VideoGigaGAN aims to provide the best of both worlds — the higher image/video quality of GAN models, with fewer flickering or distortion issues across output frames. The company has provided several examples here that show its work in full resolution.

Some of the finer details in the demo clips Adobe provided appear to be entirely artificial, such as the skin texture and creases in the below example, but the results appear impressively natural. It would be difficult to tell that generative AI was used to improve the resolution, which could extend the “what is a photo” debate to include video.

1/ OpenAI researchers have proposed a new instruction hierarchy approach to reduce the vulnerability of large language models (LLMs) to prompt injection attacks and jailbreaks.

OpenAI researchers propose an instruction hierarchy for AI language models. It is intended to reduce vulnerability to prompt injection attacks and jailbreaks. Initial results are promising.

Language models (LLMs) are vulnerable to prompt injection attacks and jailbreaks, where attackers replace the model’s original instructions with their own malicious prompts.

Continue reading “OpenAI’s new ‘instruction hierarchy’ could make AI models harder to fool” »